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Sand Box Assignment 3

Mini Project 2-

Python, Twitter and Data visualisation

The following assignment is based upon the Sandbox guest lectures on python, twitter and Datavisualisation. This is a programming and analysis assignment as such you are expected to liberallycomment your code to describe what you are doing at each step, how you identify the sender of eachtweet, and how you avoided naming each tweet sender more than once.

You will be required to run a demonstration of yourcode andexplain howitworks as part of yourassessment.

Issue Date 19th

December 2012

Submission Date 22nd

January 2012

Resources for this assignment can be found on my webpage

http://doc.gold.ac.uk/~mas01jo/

1.

Using the Twitter API and a Python script or otherwise, search for up to 1500 recent tweetsaround a particular event or topic based hashtag. (Try to

identify a hashtag that has a "small"number of participants (10s to 100s) who send tweets to each other at least some of the time.

Examples might be hastags on the following subjects:

Politics, Football fans, Online Debates, fan Reviews, events.

20Marks

2.

Write a Python routine that will loop through each of the search results, identify the distinct userswho sent the tweet and a count of the number of tweets send by each of them in the sample youcollected.

15 Marks

3.

Extend your program to printout (or save to a file) a sorted league table showing the top 10tweeters, along with their rank position by tweet volume and a count of the number of tweets theysent.

15 Marks

4.

Visualise this data using datawrapper.de or a spreadsheet programme suchas Google Sheets toproduce a bar chart showing the top 10 tweeters along with the number of tweets each of themsent.

10 Marks

5.

Optional extension: Tweets that start with a Twitter ID may be thought of as "conversational",specifically tweets that are referred to one user by another who starts a tweet with that particularuser's name. For each "conversational" tweet, extract who sent the tweet and to whom, andproduce two more league tables:

i)

showing an ordered ranking of who sent the most conversational tweets

ii)

showing an ordered ranking of who received the most conversational tweets.

20 Marks

6.

Identify how many unique (sender,receiver) pairings there are in your sample (a weak measure ofconversational diversity), and produce an ordered league table that displays how many times eachconversational pairing was observed in the sampled dataset.